All entries for Monday 09 December 2019

Thoughts on the 1st lecture session

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Dear all,

[1] today in the lecture, we saw that it was not entirely simple to install your own ML machine with Tensorflow/Keras and FastAI. I have now made a blog entry on how to do this. You can find it here.

[2] In addition, when running the FastAI code, we saw that it might take a long time even for just the pets categorization. I just ran the pets notebook (please download a new version) and have made the pets-stage-1 and pets-stage-1-50 trained models available on the download area. You need to move these models into where FastAI keeps them which in my set-up is

/home/phsht/.fastai/data/oxford-iiit-pet/images/models

Just copy the twp .pth files there and you should be able to run the pets code after the

learn.load('pets-stage-1')

fastai commands in the notebook.

[3] When you "play" with the notebook called "FastAI-lesson2-download.ipynb", note that the file data.zip contains the cats/teddys/wolves that I managed to download and use for the exercise.

[4] Some of you argued that your own machines may not be able to do meaningful ML as you do not have a GPU. Have a look at what the FastAI guys have collected in terms of possible free GPU instances, i.e. Using a GPU. I have not yet used any of these services, but would be keen to learn from your experiences!

OK, keep checking this blog for up-to-date information before we meet again next week.

Rudo Roemer : 09 Dec 2019 16:29 |  Tags: Fastai Keras Machine-Learning Tensorflow |  Comments (2) |  Close comments |  Report a problem